\section{Conclusion}
\paragraph{}Existing literature explains a number of reputation
systems which are well suited to the task of providing incentives for
truthful feedback in market-based situations.  However, a classroom
setting (ideally) does not have the same type of market-based
transactions but is instead a more obligatory environment where
students are required to submit assignments.  In an anonymous grading
system, students cannot choose the grader who will grade their
assignment, whereas in a market environment buyers are free to choose
from available vendors. However, some elements of the employed
reputation mechanisms were useful for this project.

\paragraph{}The system detailed in this paper is a starting point for 
the development of a sound, anonymous, reputation-weighted grading 
system which will significantly lighten the load of professors and TA's 
and improve educational efficacy.  The implementation of CLAPTRAP in 
Django can provide a starting point for the further development of such 
a system, and can serve as a sandbox for testing various iterations and 
configurations of our algorithm.  It is our hope that by presenting both 
this paper and the web application, we can encourage further work into 
this potentially useful concept.

